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<h1>EAMathHelp</h1>

<h2>Introduction</h2>
<p>EAMathHelp provides fast floating point math primitives. It is not a vector/matrix math library such as those in use around Electronic Arts, but rather is a base 
    for doing floating point characterizations and for doing fast floating point conversions. The former often serve to help implement the latter.</p>
<p>The constants listed below may look odd if you aren't familiar with the standardized IEEE floating point format. A description of this format is outside the scope 
    of this document, but you can find plenty of documentation about it by looking it up on the Internet. Suffice it to say the floating point numbers are essentially 
    bitfields that specify a sign, an integer value (mantissa), and an exponent to raise the integer value by.</p>
<h2>Constants</h2>
<pre class="code-example"><span class="code-example-comment">// 32 bit float bits
</span>const uint32_t  kFloat32SignMask                = UINT32_C(0x80000000);
const uint32_t  kFloat32ExponentMask            = UINT32_C(0x7F800000);
const uint32_t  kFloat32MantissaMask            = UINT32_C(0x007FFFFF);
const uint32_t  kFloat32SignAndExponentMask     = UINT32_C(0xFF800000);
const uint32_t  kFloat32SignAndMantissaMask     = UINT32_C(0x807FFFFF);
const uint32_t  kFloat32ExponentAndMantissaMask = UINT32_C(0x7FFFFFFF);
const uint32_t  kFloat32PositiveInfinityBits    = UINT32_C(0x7F800000);
const unsigned  kFloat32SignBits                = 1;
const unsigned  kFloat32ExponentBits            = 8;
const unsigned  kFloat32MantissaBits            = 23;
const unsigned  kFloat32BiasValue               = 127;
 
<span class="code-example-comment">// 64 bit float bits
</span>const uint64_t  kFloat64SignMask                = UINT64_C(0x8000000000000000);
const uint64_t  kFloat64ExponentMask            = UINT64_C(0x7FF0000000000000);
const uint64_t  kFloat64MantissaMask            = UINT64_C(0x000FFFFFFFFFFFFF);
const uint64_t  kFloat64SignAndExponentMask     = UINT64_C(0xFFF0000000000000);
const uint64_t  kFloat64SignAndMantissaMask     = UINT64_C(0x800FFFFFFFFFFFFF);
const uint64_t  kFloat64ExponentAndMantissaMask = UINT64_C(0x7FFFFFFFFFFFFFFF);
const uint64_t  kFloat64PositiveInfinityBits    = UINT64_C(0x7FF0000000000000);
const unsigned  kFloat64SignBits                = 1;
const unsigned  kFloat64ExponentBits            = 11;
const unsigned  kFloat64MantissaBits            = 52;
const unsigned  kFloat64BiasValue               = 1023;

const float32_t kFloat32Infinity                = kFloat32PositiveInfinityBits;
const float64_t kFloat64Infinity                = kFloat64PositiveInfinityBits;
 
<span class="code-example-comment">// bias to integer
</span>const float32_t kFToIBiasF32 = uint32_t(3) << 22;
const int32_t   kFToIBiasS32 = 0x4B400000;           <span class="code-example-comment">// Same as ((int32_t&) kFToIBiasF32), but known to optimizer at compile time.</span>
const float64_t kFToIBiasF64 = uint64_t(3) << 52;
 
<span class="code-example-comment">// bias to 8-bit fraction
</span>const float32_t kFToI8BiasF32 = uint32_t(3) << 14;
const int32_t   kFToI8BiasS32 = 0x47400000;          <span class="code-example-comment">// Same as ((int32_t&) kFToI8BiasF32), but known to optimizer at compile time.</span>
 
<span class="code-example-comment">// bias to 16-bit fraction
</span>const float32_t kFToI16BiasF32 = uint32_t(3) << 6;
const int32_t   kFToI16BiasS32 = 0x43400000;         <span class="code-example-comment">// Same as ((int32_t&) kFToI16BiasF32), but known to optimizer at compile time.</span>
</pre>
<h2>Functions</h2>
<p>Float conversion functions</p>
<pre class="code-example"><span class="code-example-comment">///////////////////////////////////////////////////////////////////////
// Full range conversion functions
//
// These are good for floats within the full range of a float. Remember
// that a single-precision float only has a 24-bit significand so
// most integers |x| > 2^24 cannot be represented exactly.
//
// The result of converting an out-of-range number, infinity, or NaN
// is undefined.
//
</span>inline uint32_t RoundToUint32(float fValue);
inline int32_t  RoundToInt32(float fValue);
inline int32_t  FloorToInt32(float fValue);
inline int32_t  CeilToInt32(float fValue);
inline int32_t  TruncateToInt32(float fValue);

<span class="code-example-comment">///////////////////////////////////////////////////////////////////////
// Partial range conversion functions.
//
// These are only good for |x| &lt;= 2^23. The result of converting an
// out-of-range number, infinity, or NaN is undefined.
//
</span>inline int32_t FastRoundToInt23(float fValue);


<span class="code-example-comment">///////////////////////////////////////////////////////////////////////
// Unit-to-byte functions.
//
// Converts real values in the range |x| &lt;= 1 to unsigned 8-bit values
// [0, 255]. The result of calling UnitFloatToUint8() with |x|>1 is
// undefined.
//
</span>inline uint8_t UnitFloatToUint8(float fValue);
inline uint8_t ClampUnitFloatToUint8(float fValue);

</pre>
<p>Float characterization functions</p>
<pre class="code-example"><span class="code-example-comment">///////////////////////////////////////////////////////////////////////
// IsInvalid
//
// Returns true if a value does not obey normal arithmetic rules;
// specifically, x != x. In the case of Visual C++ 2003, this is true
// for NaNs and indefinites, and not for normalized finite values,
// denormals, and infinities. Other compilers may return different
// results or even false for all values.
//
// IsInvalid() is useful as a fast assert check that floats are
// sane and won't poison computations as NaNs can with masked
// exceptions.
//
</span>inline bool IsInvalid(float32_t fValue);
inline bool IsInvalid(float64_t fValue);
 
<span class="code-example-comment">///////////////////////////////////////////////////////////////////////////////
// IsNormal
//
// Returns true if the value is a normalized finite number. That is, it is neither
// an infinite, nor a NaN (including indefinite NaN), nor a denormalized number.
// You generally want to write math operation checking code that asserts for 
// IsNormal() as opposed to checking specifically for IsNaN, etc.
//
// Normal values are defined as any floating point value with an exponent in 
// the range of [1, 254], as 0 is reserved for denormalized (underflow) values 
// and 255 is reserved for infinite (overflow) and NaN values. 
//
</span>inline bool IsNormal(float32_t fValue);
inline bool IsNormal(float64_t fValue);
 
<span class="code-example-comment">///////////////////////////////////////////////////////////////////////////////
// IsNAN
//
// A NaN is a special kind of number that is neither finite nor infinite. 
// It is the result of doing things like the following:
//    float x = 1 * NaN;
//    float x = NaN + NaN;
//    float x = 0 / 0;
//    float x = 0 / infinite;
//    float x = infinite - infinite
//    float x = sqrt(-1);
//    float x = cos(infinite);
// Under the VC++ debugger, x will be displayed as 1.#QNAN00 or 1.#IND00 and 
// the bit representation of x will be 0x7fc00001 (in the case of 1 * NaN). 
// The 'Q' in front of NAN stands for "quiet" and means that use of that value 
// in expressions won't generate exceptions. A signaling NaN (SNAN) means that 
// use of the value would generate exceptions.
// 
// NaNs are frequently generated in physics simulations and similar mathematical 
// situations when you are simulating an object moving or turning over time but 
// the time or distance differential in the calculation is very small. 
// Also, floating point roundoff error can generate NaNs if you do things 
// like call acos(x) where you didn't take care to clamp x to &lt;= 1. You can 
// also get a NaN when memory used to store a floating point value is written 
// with random data.
//
// A curious property of NaNs is that all comparisons between NaNs return 
// false except the expression: NaN != NaN. This is so even if the bit 
// representation of the two compared NaNs are identical. Thus, with NaNs, 
// the following holds:
//    x == x is always false
//    x < y is always false
//    x > y is always false
//
// As a result, one simple way to test for a NaN without fiddling with bits is 
// to simply test for x == x. If this returns false, then you have a NaN. 
// Unfortunately, many C and C++ compilers don't obey this, so you are usually 
// stuck fiddling with bits.
//
// With a NaN, all exponent bits are 1 and the mantissa is not zero.
// If the highest fraction bit is 1, the NAN is "quiet" -- it represents
// and indeterminant operation rather than an invalid one.
//</span>
inline bool IsNAN(float32_t fValue);
inline bool IsNAN(float64_t fValue);

<span class="code-example-comment">///////////////////////////////////////////////////////////////////////////////
// IsInfinite
//
// A value is infinity if the exponent bits are all 1 and all the bits of the 
// mantissa (significand) are 0. The sign bit indicates positive or negative
// infinity. Thus, for Float32, 0x7f800000 is positive infinity and 0xff800000
// is negative infinity.
//
</span>inline bool IsInfinite(float32_t fValue);
inline bool IsInfinite(float64_t fValue);

<span class="code-example-comment">///////////////////////////////////////////////////////////////////////////////
// IsIndefinite
//
// An indefinite is a special kind of NaN that is used to signify that an 
// operation between non-NaNs generated a NaN. Other than that, it really is 
// simply another NaN.
//
</span>inline bool IsIndefinite(float32_t fValue);
inline bool IsIndefinite(float64_t fValue);

<span class="code-example-comment">///////////////////////////////////////////////////////////////////////////////
// IsDenormalized
//
// Much in the same way that infinite numbers represent an overflow, 
// denormalized numbers represent an underflow. A denormalized number is 
// indicated by an exponent with a value of zero. You get a denormalized 
// number when you do operations such as this:
//    float x = 1e-10 / 1e35;
// Under the VC++ debugger, x will be displayed as 1.4e-045#DEN and the 
// bit representation of x will be 0x00000001. Unlike infinites and NaNs, 
// you can still do math with denormalized numbers. However, the results 
// of your math will likely have a lot of imprecision. You can also get a 
// denormalized value when memory used to store a floating point value is 
// written with random data.
//
</span>inline bool IsDenormalized(float32_t fValue);
inline bool IsDenormalized(float64_t fValue);</pre>

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